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By E. J. Palomo, E. Domínguez, R. M. Luque, J. Muñoz (auth.), Joan Cabestany, Ignacio Rojas, Gonzalo Joya (eds.)

This two-volume set LNCS 6691 and 6692 constitutes the refereed lawsuits of the eleventh foreign Work-Conference on synthetic Neural Networks, IWANN 2011, held in Torremolinos-Málaga, Spain, in June 2011. The 154 revised papers have been conscientiously reviewed and chosen from 202 submissions for presentation in volumes. the second one quantity comprises seventy six papers prepared in topical sections on video and photograph processing; hybrid man made neural networks: types, algorithms and information; advances in computing device studying for bioinformatics and computational biomedicine; biometric structures for human-machine interplay; information mining in biomedicine; bio-inspired combinatorial optimization; using evolutionary computation and nature-inspired algorithms to formal tools; fresh advances on fuzzy good judgment and delicate computing functions; new advances in conception and purposes of ICA-based algorithms; organic and bio-inspired dynamical structures; and interactive and cognitive environments. The final part comprises nine papers from the overseas Workshop on clever structures for Context-Based details Fusion, ISCIF 2011, held at IWANN 2011.

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Extra resources for Advances in Computational Intelligence: 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Torremolinos-Málaga, Spain, June 8-10, 2011, Proceedings, Part II

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Jos´e Luis Mart´ınez, Alberto Corrales-Garc´ıa, Pedro Cuenca, and Francisco Jos´e Quiles On the Use of Genetic Algorithms to Improve Wavelet Sign Coding Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . Ricardo Garc´ıa, Otoniel L´ opez, Antonio Mart´ı, and Manuel P. Malumbres Kernel-Based Object Tracking Using a Simple Fuzzy Color Histogram . . . . . . . . . . . . . . . . .

Let M be the incidence matrix of dimensions p × q, where p is the number of tracked objects and q the number of detected objects by the segmentation phase. Each cell bij is a binary value which represents a matching between two elements. The ideal incidence matrix matches all the tracked and segmented objects as a bijective function one by one. Thus, both the number of segmented objects not associated to any tracked objects Feature Weighting in Competitive Learning 21 or associated to more than one (M ), and the number of tracked objects with no matching or more than one to the segmented objects (N ) are penalised in the fitness function.

N. -V. Luong, K. -G. Talbi Efficient Simulation of Spatio–temporal Dynamics in Ultrasonic Resonators . . . . . . . . . . . . . . . . . . . . . . . . . . . Pedro Alonso–Jord´ a, Jes´ us Peinado–Pinilla, Isabel P´erez–Arjona, and Victor J. S´ anchez–Morcillo GPU Implementation of a Bio-inspired Vision Model . . . . . . . . . Raquel Ure˜ na, Christian Morillas, Samuel Romero, and Francisco J. Pelayo Bipartite Graph Matching on GPU over Complete or Local Grid Neighborhoods .

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